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  • What?
  • Why?
  • How?
  • Use Cases
  • Demo

Introduction


What?


Why ?




Advantages


Use Cases




Simple Example


Steps


Itemset


Antecedent & Consequent


Support


Confidence


Lift


Data


Data Dictionary


  • invoice number
  • description
  • quantity
  • invoice date
  • unit price
  • customer id
  • country

Libraries


Preprocessing


Preprocessing


What time of day do people purchase?



How many items are purchased on an average?


Most Purchased Items


Average Order Value


Read Data


Summary


Item Frequency Plot


Generate Rules


Rules Summary


Inspect Rules



Redundant Rules


Redundant Rules


Remove Redundant Rules


What influenced purchase of product X?


What purchases did product X influence?


Top Rules


Scatter Plot


Network Plot


Things to keep in mind..


Things to keep in mind..


Summary


  • unsupervised data mining technique
  • uncovers products frequently bought together
  • creates if-then scenario rules
  • cost-effective, insightful and actionable
  • association rule mining has applications in several industries
  • directionality of rule is lost while using lift
  • confidence as a measure can be misleading